{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Matplotlib \n",
    "\n",
    "Matplotlib 是 Python 的绘图库。 它可与 NumPy 一起使用，提供了一种有效的 MatLab 开源替代方案。 它也可以和图形工具包一起使用。它有一套完全仿照MATLAB的函数形式的绘图接口，在matplotlib.pyplot模块中。这套函数接口方便MATLAB用户过度到matplotlib包。 \n",
    "\n",
    "官网： http://matplotlib.org/\n",
    "\n",
    "**配置参数**：\n",
    "\n",
    "axes:   设置坐标轴边界和表面的颜色、坐标刻度值大小和网格的显示\n",
    "\n",
    "figure:  控制dpi、边界颜色、图形大小、和子区(subplot)设置\n",
    "\n",
    "font:   字体集（font family）、字体大小和样式设置\n",
    "\n",
    "grid:   设置网格颜色和线性\n",
    "\n",
    "legend:  设置图例和其中的文本的显示\n",
    "\n",
    "line:   设置线条（颜色、线型、宽度等）和标记\n",
    "\n",
    "savefig: 可以对保存的图形进行单独设置。例如，设置渲染的文件的背景为白色。\n",
    "\n",
    "xticks和yticks: 为x,y轴的主刻度和次刻度设置颜色、大小、方向，以及标签大小。\n",
    "\n",
    "**学习资源**：\n",
    "\n",
    "- 官网资源\n",
    " 1. http://matplotlib.org/examples/index.html\n",
    " 2. http://matplotlib.org/gallery.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt  # matplotlib 库是 Python 中绘制二维和三维图表的数据可视化工具\n",
    "import numpy as np\n",
    "import math\n",
    "\n",
    "#matplotlib.rcParams['axes.unicode_minus']=False"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A Figure object is the outermost container for a matplotlib graphic, which can contain multiple Axes objects. You can think of the Figure object as a box-like container holding one or more Axes (actual plots). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, _ = plt.subplots()\n",
    "type(fig)\n",
    "plt.show()\n",
    "  # subplots：一次性创建并返回所有的子图和其 axe 对象。\n",
    "  # subplot：分开多次添加子图。每次调用返回一个子图和对应的 ax 对象。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://www.freesion.com/article/24981022058/\n",
    "we created two variables with plt.subplots(). The first is a top-level Figure object. The second is a “throwaway” variable that we don’t need just yet, denoted with an underscore. Using attribute notation, it is easy to traverse down the figure hierarchy and see the first tick of the y axis of the first Axes object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3.14159265359\n"
     ]
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111)\n",
    "  # 参数111的意思是：将画布分割成1行1列，图像画在从左到右从上到下的第1块。当只想画一张图时就使用111\n",
    "  #   https://blog.csdn.net/c_lanxiaofang/article/details/125774200\n",
    "x = np.arange(0, math.pi*2, 0.02)\n",
    "  # math.pi是 python 中 math 函数库里的一个内建函数\n",
    "  #   math.pi主要就是表示圆周率\n",
    "  #   math.pi*2：生成角度，=6.283185307179586\n",
    "y = np.sin(x)\n",
    "ax.set(title='An Example Axes', ylabel='Y-Axis', xlabel='X-Axis')\n",
    "ax.plot(x,y, color = 'lightblue')\n",
    "plt.show()\n",
    "\n",
    "# Extra：\n",
    "print(math.pi)\n",
    "  # 结果：3.141592653589793"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(121)\n",
    "  # add_subplot(121)：将画布分割成1行2列，图像画在从左到右从上到下的第1块\n",
    "  # add_subplot(3,4,11)：将画布分割成3行4列，图像画在从左到右从上到下的第11块\n",
    "ax.plot(x, y, color='lightblue', linewidth=3) \n",
    "  # LineWidth: 线宽\n",
    "  # Matlab画图线型、符号及颜色设置：\n",
    "  #   https://blog.csdn.net/LK274857347/article/details/56845818\n",
    "ax.set_xlim(0, 8)\n",
    "  # Matplotlib会自动得出沿x、y（和z轴，如果是3D图）轴显示的变量的最小值和最大值\n",
    "  #   然而，可以通过使用set_xlim()和set_ylim()函数明确地设置限制\n",
    "ax = fig.add_subplot(122)\n",
    "  # add_subplot(122)：将画布分割成1行2列，图像画在从左到右从上到下的第2块。\n",
    "ax.plot(x, y, color='lightsalmon', linewidth=3) \n",
    "ax.set_xlim(0, 8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.add_axes([0, 0, 1, 1])\n",
    "  # [left，bottom，width，height]，它表示添加到画布中的矩形区域的左下角坐标（x，y），以及宽度和高度\n",
    "ax.plot(x, y, color='lightblue', linewidth=3) \n",
    "ax.set_xlim(0, 8)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax1 = fig.add_axes([0.05, 0.05, 1, 1])\n",
    "  # 【left，bottom，width，height】，它表示添加到画布中的矩形区域的左下角坐标（x，y），以及宽度和高度\n",
    "ax1.plot(x, y, color='lightblue', linewidth=3) \n",
    "  # 回顾：\n",
    "  #   x = np.arange(0, math.pi*2, 0.02)\n",
    "  #   y = np.sin(x)\n",
    "ax1.set_title('Outer')\n",
    "\n",
    "ax2 = fig.add_axes([0.6, 0.6, 0.4, 0.4])\n",
    "  # 【left，bottom，width，height】，它表示添加到画布中的矩形区域的左下角坐标（x，y），以及宽度和高度\n",
    "ax2.plot(x, y, color = 'red', linewidth=1)\n",
    "ax2.set_title('Inner')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The prescribed way to create a Figure with a single Axes under the OO approach is (object-oriented) with plt.subplots(). This is really the only time that the OO approach uses pyplot, to create a Figure and Axes:\n",
    "在OO方法下使用单个轴创建图形的规定方式是使用plt.subplots() （不太直观plt.subplots() 。 （这确实是OO方法唯一一次使用pyplot来创建图形和轴）。 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let’s illustrate with a stacked area graph of three time series:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fixing random state for reproducibility\n",
    "np.random.seed(10000)\n",
    "  # np.random.seed()函数用于生成指定随机数\n",
    "  #   调用np.random.seed()来使（伪）随机数据的示例可重现\n",
    "  #   seed()被设置了之后，np,random.random()可以按顺序产生一组固定的数组，如果使用相同的seed()值，则每次生成的随机数都相同，如果不设置这个值，那么每次生成的随机数不同。\n",
    "x, y = np.random.randn(2, 100)\n",
    "  # 输出2行100列的二维数组，x 100个，y 100个\n",
    "  #   返回一个或一组服从标准正态分布的随机样本值\n",
    "  #   https://blog.csdn.net/weixin_43283397/article/details/106211213\n",
    "  #   https://blog.csdn.net/abc13526222160/article/details/86423754\n",
    "_, [ax1, ax2] = plt.subplots(2, 1, sharex=True)\n",
    "  # 画布被分为 2 行 1 列的两个子图区域\n",
    "  # sharex和sharey分别控制所有子图共享X轴刻度和Y轴刻度\n",
    "ax1.xcorr(x, y, usevlines=True, maxlags=50, normed=True, linewidth=2)\n",
    "  # xcorr()：返回两个离散时间序列的互相关\n",
    "  #   （1）maxlags；返回一个延迟范围在[-maxlags,maxlags]的自相关函数序列，输出的程度为 2maxlags+1\n",
    "  #   （2）usevlines=True：线条；usevlines=False：点\n",
    "  #        usevlines : bool, optional, default: True\n",
    "  #                    If True, Axes.vlines is used to plot the vertical lines from the origin to the acorr. \n",
    "  #                    Otherwise, Axes.plot is used.\n",
    "  #   （3）normed : bool, optional, default: True。If True, input vectors are normalised to unit length.\n",
    "  #    https://blog.csdn.net/lvsehaiyang1993/article/details/82913443\n",
    "  #    https://matplotlib.org/3.0.0/api/_as_gen/matplotlib.pyplot.xcorr.html\n",
    "ax1.grid(True)\n",
    "  # 显示网格线\n",
    "ax1.axhline(0, color='black', linewidth=2)\n",
    "  # 绘制平行于 x 轴的水平参考线\n",
    "  #   linewidth：参考线的线条宽度\n",
    "  #   https://blog.csdn.net/Kwoky/article/details/104781689\n",
    "ax2.acorr(x, usevlines=True, normed=True, maxlags=50, linewidth=2)\n",
    "  # acorr()：X的自相关函数\n",
    "ax2.grid(True)\n",
    "ax2.axhline(0, color='black', linewidth=2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "rng = np.arange(50)\n",
    "  # 返回一个有终点和起点的固定步长的排列（可理解为一个等差数组）\n",
    "  # [ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23\n",
    "  #   24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47\n",
    "  #   48 49]\n",
    "rnd = np.random.randint(0, 10, size=(3, rng.size))  \n",
    "  # 返回一个随机整型数：[0, 10)，size=(3,50) 3行50列\n",
    "  #   范围从低（包括）到高（不包括），即[low, high)\n",
    "  #   如果没有写参数high的值，则返回[0,low)的值\n",
    "  #   rng.size：结果：50\n",
    "yrs = 1950 + rng\n",
    "  # 从1950年开始的后50年\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(8, 5))\n",
    "ax.stackplot(yrs, rng + rnd, labels=['Eastasia', 'Eurasia', 'Oceania'])\n",
    "  # 堆积面积图、主题河流图、流图（streamgraph）\n",
    "  #   'Eastasia', 'Eurasia', 'Oceania'：东亚、欧亚大陆、大洋洲\n",
    "  #   rnd：3行50列\n",
    "  #   rng：50列\n",
    "ax.set_title('Combined debt growth over time')\n",
    "  # set_title()：设置图片的标题    \n",
    "ax.legend(loc='upper left')\n",
    "  # legend：标签\n",
    "ax.set_ylabel('Total debt')\n",
    "ax.set_xlim(xmin=yrs[0], xmax=yrs[-1])\n",
    "  # 使用set_xlim()和set_ylim()函数明确地设置限制\n",
    "  #   yrs[0]=1950，yrs[-1]=1999（最末尾项）\n",
    "#fig.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- After creating three random time series, we defined one Figure (fig) containing one Axes (a plot, ax).\n",
    "\n",
    "- We call methods of ax directly to create a stacked area chart and to add a legend, title, and y-axis label. Under the object-oriented approach, it’s clear that all of these are attributes of ax.\n",
    "\n",
    "- tight_layout() applies to the Figure object as a whole to clean up whitespace padding."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "x = np.random.randint(low=1, high=11, size=50)\n",
    "  # 返回一个随机整型数：[1, 11)，size=50 \n",
    "  #   范围从低（包括）到高（不包括），即[low, high)\n",
    "  #   如果没有写参数high的值，则返回[0,low)的值\n",
    "y = x + np.random.randint(1, 5, size=x.size)\n",
    "data = np.column_stack((x, y))\n",
    "  # np.hstack((a,b))：如果a、b是list，则在列上叠加；如果a、b是矩阵array，则在行相同时扩展列，行不变\n",
    "  # https://blog.csdn.net/zilongxuan008/article/details/121807196"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, (ax1, ax2) = plt.subplots(nrows=1, ncols=2, figsize=(8, 4))\n",
    "ax1.scatter(x=x, y=y, marker='o', c='r', edgecolor='b')\n",
    "  # scatter()：绘制散点图\n",
    "  #   marker='o'：默认，圆圈\n",
    "  #   c: 指定散点图点的颜色，默认为蓝色，此处为红色\n",
    "  #   edgecolors: 设置散点边界线的颜色，蓝色\n",
    "  #   https://blog.csdn.net/qq_41635352/article/details/79963345/?utm_medium=distribute.pc_relevant.none-task-blog-2~default~baidujs_utm_term~default-8--blog-124259514.235^v38^pc_relevant_default_base&spm=1001.2101.3001.4242.5&utm_relevant_index=11\n",
    "ax1.set_title('Scatter: $x$ versus $y$')\n",
    "ax1.set_xlabel('$x$')\n",
    "ax1.set_ylabel('$y$')\n",
    "\n",
    "ax2.hist(data, bins=np.arange(data.min(), data.max()),label=('x', 'y'))\n",
    "  # hist():\n",
    "  #   bins：设置长条形的数目。np.arange：从 1 到 14\n",
    "  #   range：指定直方图数据的上下界，默认包含绘图数据的最大值和最小值（范围）\n",
    "  #   https://blog.csdn.net/Yangyuqing_/article/details/124199993\n",
    "ax2.legend(loc=(0.7, 0.8))\n",
    "ax2.set_title('Frequencies of $x$ and $y$')\n",
    "ax2.yaxis.tick_right()\n",
    "  # 纵坐标移到右边\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There’s a little bit more going on in this example:\n",
    "\n",
    "- Because we’re creating a “1x2” Figure, the returned result of plt.subplots(1, 2) is now a Figure object and a NumPy array of Axes objects. (You can inspect this with fig, axs = plt.subplots(1, 2) and taking a look at axs.)\n",
    "\n",
    "- We deal with ax1 and ax2 individually, which would be difficult to do with the stateful approach. The final line is a good illustration of the object hierarchy, where we are modifying the yaxis belonging to the second Axes, placing its ticks and ticklabels to the right.\n",
    "\n",
    "- Text inside dollar signs utilizes TeX markup to put variables in italics."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The “response” variable y below, to use the statistical term, is an area’s average home value. pop and age are the area’s population and average house age, respectively:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x = np.linspace(0, 10, 500)\n",
    "  # np.linspace(start = 0, stop = 100, num = 5)\n",
    "  #   起始点、终止端，以及指定分隔值总数（包括起始点和终止点）\n",
    "y = np.sin(x)\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "\n",
    "# Using set_dashes() to modify dashing of an existing line\n",
    "line1, = ax.plot(x, y, label='Using set_dashes()')\n",
    "line1.set_dashes([2, 2, 10, 2])  \n",
    "  # set_dashes([2,2,10,2])：将曲线设置为点划线\n",
    "  #   set_dashes([line_space,space_space,line_space,space_space])\n",
    "  #               2pt line,  2pt break,  10pt line, 2pt break\n",
    "\n",
    "# Using plot(..., dashes=...) to set the dashing when creating a line\n",
    "line2, = ax.plot(x, y - 0.2, dashes=[6,3], label='Using the dashes parameter')\n",
    "  # dashes：以点为单位的连接/断开墨水序列\n",
    "  #         6pt line,  3pt break\n",
    "ax.legend()\n",
    "  # legend：设置图例和其中的文本的显示\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "men_means, men_std = (20, 35, 30, 35, 27), (2, 3, 4, 1, 2)\n",
    "women_means, women_std = (25, 32, 34, 20, 25), (3, 5, 2, 3, 3)\n",
    "\n",
    "ind = np.arange(len(men_means))  # the x locations for the groups\n",
    "len(men_means)\n",
    "width = 0.35  # the width of the bars\n",
    "\n",
    "fig, ax = plt.subplots()\n",
    "ax.bar(ind - width/2, men_means, width, yerr=men_std,\n",
    "                color='SkyBlue', label='Men')\n",
    "ax.bar(ind + width/2, women_means, width, yerr=women_std,\n",
    "                color='IndianRed', label='Women')\n",
    "  # ax.bar(x, height, width, bottom, align)\n",
    "  #   height 一个标量或者是标量序列，代表柱状图的高度\n",
    "  #   width 可选参数，标量或类数组，柱状图的默认宽度值为 0.8\n",
    "  #   bottom 可选参数，标量或类数组，柱状图的y坐标默认为None\n",
    "  #   xerr, yerrs: calar or array-like of shape(N,) or shape(2, N), optional.\n",
    "  #                scalar: symmetric +/- values for all bars\n",
    "  #                https://matplotlib.org/3.2.1/api/_as_gen/matplotlib.axes.Axes.bar.html\n",
    "  #   https://blog.csdn.net/weixin_45671036/article/details/112646889\n",
    "# Add some text for labels, title and custom x-axis tick labels, etc.\n",
    "ax.set_ylabel('Scores')\n",
    "ax.set_title('Scores by group and gender')\n",
    "ax.set_xticks(ind)\n",
    "  # 设置坐标轴：xticks()和yticks()函数使用一个列表对象作为参数。列表中的元素表示相应动作上显示ticks的位置\n",
    "ax.set_xticklabels(('G1', 'G2', 'G3', 'G4', 'G5'))\n",
    "ax.legend()\n",
    "  # legend：设置图例和其中的文本的显示\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib\n",
    "# sphinx_gallery_thumbnail_number = 2\n",
    "\n",
    "vegetables = [\"cucumber\", \"tomato\", \"lettuce\", \"asparagus\",\n",
    "              \"potato\", \"wheat\", \"barley\"]\n",
    "farmers = [\"Farmer Joe\", \"Upland Bros.\", \"Smith Gardening\",\n",
    "           \"Agrifun\", \"Organiculture\", \"BioGoods Ltd.\", \"Cornylee Corp.\"]\n",
    "\n",
    "harvest = np.array([[0.8, 2.4, 2.5, 3.9, 0.0, 4.0, 0.0],\n",
    "                    [2.4, 0.0, 4.0, 1.0, 2.7, 0.0, 0.0],\n",
    "                    [1.1, 2.4, 0.8, 4.3, 1.9, 4.4, 0.0],\n",
    "                    [0.6, 0.0, 0.3, 0.0, 3.1, 0.0, 0.0],\n",
    "                    [0.7, 1.7, 0.6, 2.6, 2.2, 6.2, 0.0],\n",
    "                    [1.3, 1.2, 0.0, 0.0, 0.0, 3.2, 5.1],\n",
    "                    [0.1, 2.0, 0.0, 1.4, 0.0, 1.9, 6.3]])\n",
    "fig, ax = plt.subplots()\n",
    "im = ax.imshow(harvest)\n",
    "  # subplots可以直接创建画板的格局，如下例子，subplots创建了一个2行1列排版的画布，然后用ax.imshow在排版上绘制图像。\n",
    "  # 而ax.imshow的行为是能在区域ax绘制图像，其可以接受list或者numpy.ndarray类型输入的像素点，并绘制图片。\n",
    "\n",
    "# We want to show all ticks...\n",
    "ax.set_xticks(np.arange(len(farmers)))\n",
    "ax.set_yticks(np.arange(len(vegetables)))\n",
    "# ... and label them with the respective list entries\n",
    "ax.set_xticklabels(farmers)\n",
    "ax.set_yticklabels(vegetables)\n",
    "\n",
    "# Rotate the tick labels and set their alignment. \n",
    "# setp: set property\n",
    "plt.setp(ax.get_xticklabels(), rotation=45, ha=\"right\",\n",
    "         rotation_mode=\"anchor\")\n",
    "\n",
    "# Loop over data dimensions and create text annotations.\n",
    "for i in range(len(vegetables)):\n",
    "    for j in range(len(farmers)):\n",
    "        text = ax.text(j, i, harvest[i, j],\n",
    "                       ha=\"center\", va=\"center\", color=\"w\")\n",
    "\n",
    "ax.set_title(\"Harvest of local farmers (in tons/year)\")\n",
    "fig.tight_layout()\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lPUCpvte1joVcYrqFCtA2UeVJ9wbWWzMXzCTV6bYtXJCb/jl9ZZJY2VG1UDtP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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1234c630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Create some mock data\n",
    "t = np.arange(0.01, 10.0, 0.01)\n",
    "data1 = np.exp(t)\n",
    "data2 = np.sin(2 * np.pi * t)\n",
    "\n",
    "fig, ax1 = plt.subplots()\n",
    "\n",
    "color = 'tab:red'\n",
    "ax1.set_xlabel('time (s)')\n",
    "ax1.set_ylabel('exp', color=color)\n",
    "ax1.plot(t, data1, color=color)\n",
    "ax1.tick_params(axis='y', labelcolor=color)\n",
    "\n",
    "ax2 = ax1.twinx()  # instantiate a second axes that shares the same x-axis\n",
    "\n",
    "color = 'tab:blue'\n",
    "ax2.set_ylabel('sin', color=color)  # we already handled the x-label with ax1\n",
    "ax2.plot(t, data2, color=color)\n",
    "ax2.tick_params(axis='y', labelcolor=color)\n",
    "\n",
    "fig.tight_layout()  # otherwise the right y-label is slightly clipped\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Fixing random state for reproducibility\n",
    "np.random.seed(19680801)\n",
    "\n",
    "# Compute areas and colors\n",
    "N = 150\n",
    "r = 2 * np.random.rand(N)\n",
    "theta = 2 * np.pi * np.random.rand(N)\n",
    "area = 200 * r**2\n",
    "colors = theta\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='polar') # “111”表示“1×1网格，第一子图”\n",
    "  # projection='polar': 极坐标绘图需要在创建子图的时候设置参数projection=\"polar\"\n",
    "  #   https://blog.csdn.net/hustlei/article/details/122502686\n",
    "c = ax.scatter(theta, r, c=colors, s=area, cmap='hsv', alpha=0.75)\n",
    "  # https://blog.csdn.net/qq_41635352/article/details/79963345?ops_request_misc=%257B%2522request%255Fid%2522%253A%2522169746561416800182142408%2522%252C%2522scm%2522%253A%252220140713.130102334..%2522%257D&request_id=169746561416800182142408&biz_id=0&utm_medium=distribute.pc_search_result.none-task-blog-2~all~baidu_landing_v2~default-8-79963345-null-null.142^v96^pc_search_result_base8&utm_term=ax.scatter&spm=1018.2226.3001.4187\n",
    "plt.show() "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# This import registers the 3D projection, but is otherwise unused.\n",
    "from mpl_toolkits.mplot3d import Axes3D  # noqa: F401 unused import\n",
    "\n",
    "# Fixing random state for reproducibility\n",
    "np.random.seed(19680801)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "\n",
    "colors = ['r', 'g', 'b', 'y']\n",
    "yticks = [3, 2, 1, 0]\n",
    "for c, k in zip(colors, yticks):\n",
    "    # Generate the random data for the y=k 'layer'.\n",
    "    xs = np.arange(20)\n",
    "    ys = np.random.rand(20)\n",
    "\n",
    "    # You can provide either a single color or an array with the same length as\n",
    "    # xs and ys. To demonstrate this, we color the first bar of each set cyan.\n",
    "    cs = [c] * len(xs)\n",
    "    cs[0] = 'c'\n",
    "\n",
    "    # Plot the bar graph given by xs and ys on the plane y=k with 80% opacity.\n",
    "    ax.bar(xs, ys, zs=k, zdir='y', color=cs, alpha=0.8)\n",
    "\n",
    "ax.set_xlabel('X')\n",
    "ax.set_ylabel('Y')\n",
    "ax.set_zlabel('Z')\n",
    "\n",
    "# On the y axis let's only label the discrete values that we have data for.\n",
    "ax.set_yticks(yticks)\n",
    "\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.15"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
